Title :
Biological information fusion using a PCNN and belief filtering
Author_Institution :
SNAT, Air Force Res. Lab., Wright-Patterson AFB, OH, USA
Abstract :
Biological information fusion results from the combination of sensed current and learned past information. The paper focuses on modeling visual cortex information fusion where a pulse coupled neural network simulates the linking procedure to segment related spatial information of the primary visual cortex and a belief filter to confirm target identity with movement information of the medial temporal cortex
Keywords :
brain models; feature extraction; filtering theory; neural nets; physiological models; sensor fusion; visual perception; belief filtering; biological information fusion; learned past information; linking procedure; medial temporal cortex; movement information; pulse coupled neural network; sensed current information; spatial information; target identity; visual cortex information fusion; Biological system modeling; Brain modeling; Data mining; Feature extraction; Fuses; Information filtering; Information filters; Joining processes; Neural networks; Visual system;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.833523
